A system‐level optimization framework for efficiency and effectiveness improvement of wastewater treatment plants

Abstract

Wastewater treatment plants constitute an essential part of the sewage system. They have the role of removing pollutants from wastewater to enable the safe disposal of the treated effluent in the natural environment. This research seeks to evaluate plants' efficiency and effectiveness, which involves minimizing energy consumption while obtaining a quality level of the treated water aligned with legislation requirements. We explore two policy scenarios regarding the measurement of effluent quality. The first assumes that pollutants' emission quotas (EQs) are fixed at each plant. The second assumes that quotas are set for the receiving waters (e.g., river or watercourse in the natural environment) so that trade‐offs in EQs among plants sharing the same discharge site are possible. This latter scenario requires a system‐wide analysis to identify optimal targets for pollutants removal at each plant that allow fulfilling the expected average quality levels of the effluent discharged. This paper develops a methodology to fully realize the potential for energy savings based on an innovative mixed‐integer linear programming model. This model follows the data envelopment analysis axioms to estimate the frontier of the production possibility set. The approach proposed is tested in a real‐world context using the plants of a Portuguese water company. The results show that the two scenarios combining efficiency and effectiveness perspectives have advantages in terms of energy savings compared to the conventional situation focused only on efficiency gains. The saving potential is slightly higher in the scenario allowing reallocation of EQs among plants.

Early Warning System for Urban Industrial Wastewater based on Remote Sensing Technology and Image Analysis

“…(5) The data of the system must be open to the national environmental protection regulatory authorities to facilitate their inspection in real time. (6) Shall not do anything to harm the national interest, treat the data realistically and shall not be falsified.…”

“…In this paper, a scheme to construct an early warning system for urban industrial wastewater based on remote sensing technology and image analysis technology is proposed, which can effectively identify pollutants in the environment by using the characteristics of remote sensing images [5] and applying them to the monitoring of urban environmental pollution, and can judge the degree of pollution by its concentration, flow rate, and other indicators to provide early warning of urban industrial wastewater pollutant discharge indicators [6][7].…”

Water Pollution Early Warning Model Based on Decision Tree Algorithm and Electronic Information Technology

“…water functions differently [11]. Water pollution incidents of the same scale and degree of pollution also have different pollution consequences; if urban and rural water pollution incidents are of the same scale and degree, the consequences of the damage can be very different, with urban damage being much greater than rural damage and the negative impacts of urban water pollution being higher than rural [12][13].…”